Papers by Azadeh Shakery
PerCul: A Story-Driven Cultural Evaluation of LLMs in Persian (2025.naacl-long)
Copied to clipboard
Erfan Moosavi Monazzah, Vahid Rahimzadeh, Yadollah Yaghoobzadeh, Azadeh Shakery, Mohammad Taher Pilehvar
| Challenge: | Large language models predominantly reflect Western cultures due to the dominance of English-centric training data. |
| Approach: | They propose a dataset to assess the sensitivity of LLMs to Persian culture. |
| Outcome: | The proposed model shows a 11.3% gap between best closed-source model and layperson baseline while the gap increases to 21.3% by using the best open-weight model. |
ARMAN: Pre-training with Semantically Selecting and Reordering of Sentences for Persian Abstractive Summarization (2021.emnlp-main)
Copied to clipboard
| Challenge: | Abstractive summarization is one of the areas influenced by pre-trained language models. |
| Approach: | They propose a Transformer-based encoder-decoder model pre-trained with three novel objectives to address this issue. |
| Outcome: | The proposed model outperforms previous models on six Persian summarization tasks . it also outperformed previous models in textual entailment, question paraphrasing, and question answering . |
PolitiSky24: U.S. Political Bluesky Dataset with User Stance Labels (2025.findings-emnlp)
Copied to clipboard
| Challenge: | Stance detection is a method of identifying the viewpoint expressed in text toward a specific target, such as a political figure. |
| Approach: | They present a dataset for the 2024 U.S. presidential election that includes 16,044 user-target stance pairs enriched with engagement metadata, interaction graphs, and user posting histories. |
| Outcome: | The proposed dataset comprises 16,044 user-target stance pairs enriched with engagement metadata, interaction graphs, and user posting histories. |